henhaobio
Sign in

mAbsBioinformaticsPeer-reviewed journal article

Ab-Ligity: Identifying sequence-dissimilar antibodies that bind to the same epitope

Wing Ki WongiD, Sarah A. RobinsoniD, Alexander BujotzekiD, Guy J. GeorgesiD, Alan P. Lewis, Jiye ShiiD, James SnowdeniD, Bruck TaddeseiD, Charlotte Mary DeaneiD

PDFDOIPreprint

Abstract

Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. We present Ab-Ligity, a structure-based similarity measure tailored to antibody-antigen interfaces. Using predicted paratopes on model antibody structures, we assessed its ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset of antibodies whose sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (precision of 0.95 and recall of 0.69). We compared Ab-Ligitys performance to an existing tool for comparing general protein interfaces, InterComp, and showed improved performance on antibody cases alongside a significant speed-up. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. The tool is available at http://opig.stats.ox.ac.uk/resources.

Citations
46
FWCI
2.51
Field percentile
top 9%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMahita '25Spoendlin '23McCoy '24Lee '26Akbar '20Raybould '20
72% semantic matchBioinformatics
Jarjapu Mahita, Haeuk Kim, Marcus Fabiano de Almeida Mendes+5 more·bioRxiv·May 24, 2025· 1 citations